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Abstract
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Transportation sector is an important component of the economy having a remarkable impact on the welfare of the population. Also, this important sector is one of the major consumers of petroleum products, and hence, a great contributor to the existing greenhouse gases and CO2 in the air. In recent years, the rising number of cars results in a growing number of traffic-related problems, including congestion and pollution. It is commonly known that as traffic congestion increases, CO2 emissions also increase. It can be lowered by improving traffic operations.
One of the important problems to improve efficiency of transportation is vehicle routing problem. Considering the congestion of traffic in vehicle routing problem is essential due to the daily increase in traffic congestion. Time dependent vehicle routing is the most appropriate approach to face traffic issue in vehicle routing problem.
The aim of this study is to propose an optimization model based on traffic congestion to improve both economic and ecological indicators. To achieve this, two new approaches in time-dependent vehicle routing problems are used. The approach includes using alternative strategies for speed, stop time at the node, and the departure time from the depot in order to improve in the routing of the vehicle. The modelling approach of this research is mixed integer programming. In order to solve the model, a two phased heuristic approach is implemented.
To show the improvements, a real example of a distribution company in Bushehr is used. Findings indicate considering criteria such as tour time, total routing time, the speed on the network, and emission produced, the proposed model is able to find an optimum solution.
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